Search results for: video classification
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1490

Search results for: video classification

650 Improvement of the Q-System Using the Rock Engineering System: A Case Study of Water Conveyor Tunnel of Azad Dam

Authors: S. Golmohammadi, M. Noorian Bidgoli

Abstract:

Because the status and mechanical parameters of discontinuities in the rock mass are included in the calculations, various methods of rock engineering classification are often used as a starting point for the design of different types of structures. The Q-system is one of the most frequently used methods for stability analysis and determination of support systems of underground structures in rock, including tunnel. In this method, six main parameters of the rock mass, namely, the Rock Quality Designation (RQD), joint set number (Jn), joint roughness number (Jr), joint alteration number (Ja), joint water parameter (Jw) and Stress Reduction Factor (SRF) are required. In this regard, in order to achieve a reasonable and optimal design, identifying the effective parameters for the stability of the mentioned structures is one of the most important goals and the most necessary actions in rock engineering. Therefore, it is necessary to study the relationships between the parameters of a system and how they interact with each other and, ultimately, the whole system. In this research, it has been attempted to determine the most effective parameters (key parameters) from the six parameters of rock mass in the Q-system using the Rock Engineering System (RES) method to improve the relationships between the parameters in the calculation of the Q value. The RES system is, in fact, a method by which one can determine the degree of cause and effect of a system's parameters by making an interaction matrix. In this research, the geomechanical data collected from the water conveyor tunnel of Azad Dam were used to make the interaction matrix of the Q-system. For this purpose, instead of using the conventional methods that are always accompanied by defects such as uncertainty, the Q-system interaction matrix is coded using a technique that is actually a statistical analysis of the data and determining the correlation coefficient between them. So, the effect of each parameter on the system is evaluated with greater certainty. The results of this study show that the formed interaction matrix provides a reasonable estimate of the effective parameters in the Q-system. Among the six parameters of the Q-system, the SRF and Jr parameters have the maximum and minimum impact on the system, respectively, and also the RQD and Jw parameters have the maximum and minimum impact on the system, respectively. Therefore, by developing this method, we can obtain a more accurate relation to the rock mass classification by weighting the required parameters in the Q-system.

Keywords: Q-system, Rock Engineering System, statistical analysis, rock mass, tunnel.

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649 Cutting and Breaking Events in Telugu

Authors: Vasanta Duggirala, Y. Viswanatha Naidu

Abstract:

This paper makes a contribution to the on-going debate on conceptualization and lexicalization of cutting and breaking (C&B) verbs by discussing data from Telugu, a language of India belonging to the Dravidian family. Five Telugu native speakers- verbalizations of agentive actions depicted in 43 short video-clips were analyzed. It was noted that verbalization of C&B events in Telugu requires formal units such as simple lexical verbs, explicator compound verbs, and other complex verb forms. The properties of the objects involved, the kind of instruments used, and the manner of action had differential influence on the lexicalization patterns. Further, it was noted that all the complex verb forms encode 'result' and 'cause' sub-events in that order. Due to the polysemy associated with some of the verb forms, our data does not support the straightforward bipartition of this semantic domain.

Keywords: Cluster analysis, Cutting and breaking events, Polysemy, Semantic extension, Telugu.

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648 Digital Cinema Watermarking State of Art and Comparison

Authors: H. Kelkoul, Y. Zaz

Abstract:

Nowadays, the vigorous popularity of video processing techniques has resulted in an explosive growth of multimedia data illegal use. So, watermarking security has received much more attention. The purpose of this paper is to explore some watermarking techniques in order to observe their specificities and select the finest methods to apply in digital cinema domain against movie piracy by creating an invisible watermark that includes the date, time and the place where the hacking was done. We have studied three principal watermarking techniques in the frequency domain: Spread spectrum, Wavelet transform domain and finally the digital cinema watermarking transform domain. In this paper, a detailed technique is presented where embedding is performed using direct sequence spread spectrum technique in DWT transform domain. Experiment results shows that the algorithm provides high robustness and good imperceptibility.

Keywords: Digital cinema, watermarking, wavelet, spread spectrum, JPEG2000.

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647 A Robust Visual Tracking Algorithm with Low-Rank Region Covariance

Authors: Songtao Wu, Yuesheng Zhu, Ziqiang Sun

Abstract:

Region covariance (RC) descriptor is an effective and efficient feature for visual tracking. Current RC-based tracking algorithms use the whole RC matrix to track the target in video directly. However, there exist some issues for these whole RCbased algorithms. If some features are contaminated, the whole RC will become unreliable, which results in lost object-tracking. In addition, if some features are very discriminative to the background, other features are still processed and thus reduce the efficiency. In this paper a new robust tracking method is proposed, in which the whole RC matrix is decomposed into several low rank matrices. Those matrices are dynamically chosen and processed so as to achieve a good tradeoff between discriminability and complexity. Experimental results have shown that our method is more robust to complex environment changes, especially either when occlusion happens or when the background is similar to the target compared to other RC-based methods.

Keywords: Visual tracking, region covariance descriptor, lowrankregion covariance

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646 Research on Software Security Testing

Authors: Gu Tian-yang, Shi Yin-sheng, Fang You-yuan

Abstract:

Software security testing is an important means to ensure software security and trustiness. This paper first mainly discusses the definition and classification of software security testing, and investigates methods and tools of software security testing widely. Then it analyzes and concludes the advantages and disadvantages of various methods and the scope of application, presents a taxonomy of security testing tools. Finally, the paper points out future focus and development directions of software security testing technology.

Keywords: security testing, security functional testing, securityvulnerability testing, testing method, testing tool

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645 Development of Monitoring and Simulation System of Human Tracking System Based On Mobile Agent Technologies

Authors: Kozo Tanigawa, Toshihiko Sasama, Kenichi Takahashi, Takao Kawamura, Kazunori Sugahara

Abstract:

In recent years, the number of the cases of information leaks is increasing. Companies and Research Institutions make various actions against information thefts and security accidents. One of the actions is adoption of the crime prevention system, including the monitoring system by surveillance cameras. In order to solve difficulties of multiple cameras monitoring, we develop the automatic human tracking system using mobile agents through multiple surveillance cameras to track target persons. In this paper, we develop the monitor which confirms mobile agents tracing target persons, and the simulator of video picture analysis to construct the tracking algorithm.

Keywords: Human tracking, mobile agent, monitoring, simulate.

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644 Rapid Monitoring of Earthquake Damages Using Optical and SAR Data

Authors: Saeid Gharechelou, Ryutaro Tateishi

Abstract:

Earthquake is an inevitable catastrophic natural disaster. The damages of buildings and man-made structures, where most of the human activities occur are the major cause of casualties from earthquakes. A comparison of optical and SAR data is presented in the case of Kathmandu valley which was hardly shaken by 2015-Nepal Earthquake. Though many existing researchers have conducted optical data based estimated or suggested combined use of optical and SAR data for improved accuracy, however finding cloud-free optical images when urgently needed are not assured. Therefore, this research is specializd in developing SAR based technique with the target of rapid and accurate geospatial reporting. Should considers that limited time available in post-disaster situation offering quick computation exclusively based on two pairs of pre-seismic and co-seismic single look complex (SLC) images. The InSAR coherence pre-seismic, co-seismic and post-seismic was used to detect the change in damaged area. In addition, the ground truth data from field applied to optical data by random forest classification for detection of damaged area. The ground truth data collected in the field were used to assess the accuracy of supervised classification approach. Though a higher accuracy obtained from the optical data then integration by optical-SAR data. Limitation of cloud-free images when urgently needed for earthquak evevent are and is not assured, thus further research on improving the SAR based damage detection is suggested. Availability of very accurate damage information is expected for channelling the rescue and emergency operations. It is expected that the quick reporting of the post-disaster damage situation quantified by the rapid earthquake assessment should assist in channeling the rescue and emergency operations, and in informing the public about the scale of damage.

Keywords: Sentinel-1A data, Landsat-8, earthquake damage, InSAR, rapid monitoring, 2015-Nepal earthquake.

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643 Clustered Signatures for Modeling and Recognizing 3D Rigid Objects

Authors: H. B. Darbandi, M. R. Ito, J. Little

Abstract:

This paper describes a probabilistic method for three-dimensional object recognition using a shared pool of surface signatures. This technique uses flatness, orientation, and convexity signatures that encode the surface of a free-form object into three discriminative vectors, and then creates a shared pool of data by clustering the signatures using a distance function. This method applies the Bayes-s rule for recognition process, and it is extensible to a large collection of three-dimensional objects.

Keywords: Object recognition, modeling, classification, computer vision.

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642 Person Identification using Gait by Combined Features of Width and Shape of the Binary Silhouette

Authors: M.K. Bhuyan, Aragala Jagan.

Abstract:

Current image-based individual human recognition methods, such as fingerprints, face, or iris biometric modalities generally require a cooperative subject, views from certain aspects, and physical contact or close proximity. These methods cannot reliably recognize non-cooperating individuals at a distance in the real world under changing environmental conditions. Gait, which concerns recognizing individuals by the way they walk, is a relatively new biometric without these disadvantages. The inherent gait characteristic of an individual makes it irreplaceable and useful in visual surveillance. In this paper, an efficient gait recognition system for human identification by extracting two features namely width vector of the binary silhouette and the MPEG-7-based region-based shape descriptors is proposed. In the proposed method, foreground objects i.e., human and other moving objects are extracted by estimating background information by a Gaussian Mixture Model (GMM) and subsequently, median filtering operation is performed for removing noises in the background subtracted image. A moving target classification algorithm is used to separate human being (i.e., pedestrian) from other foreground objects (viz., vehicles). Shape and boundary information is used in the moving target classification algorithm. Subsequently, width vector of the outer contour of binary silhouette and the MPEG-7 Angular Radial Transform coefficients are taken as the feature vector. Next, the Principal Component Analysis (PCA) is applied to the selected feature vector to reduce its dimensionality. These extracted feature vectors are used to train an Hidden Markov Model (HMM) for identification of some individuals. The proposed system is evaluated using some gait sequences and the experimental results show the efficacy of the proposed algorithm.

Keywords: Gait Recognition, Gaussian Mixture Model, PrincipalComponent Analysis, MPEG-7 Angular Radial Transform.

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641 Balancing Tourism and Environment: The ETM Model

Authors: U.V Jose, Muhammed Nahar, Vijayakumar S., Sonia Jose

Abstract:

Environment both endowed and built are essential for tourism. However tourism and environment maintains a complex relationship, where in most cases environment is at the receiving end. Many tourism development activities have adverse environmental effects, mainly emanating from construction of general infrastructure and tourism facilities. These negative impacts of tourism can lead to the destruction of precious natural resources on which it depends. These effects vary between locations; and its effect on a hill destination is highly critical. This study aims at developing a Sustainable Tourism Planning Model for an environmentally sensitive tourism destination in Kerala, India. Being part of the Nilgiri mountain ranges, Munnar falls in the Western Ghats, one of the biological hotspots in the world. Endowed with a unique high altitude environment Munnar inherits highly significant ecological wealth. Giving prime importance to the protection of this ecological heritage, the study proposes a tourism planning model with resource conservation and sustainability as the paramount focus. Conceiving a novel approach towards sustainable tourism planning, the study proposes to assess tourism attractions using Ecological Sensitivity Index (ESI) and Tourism Attractiveness Index (TAI). Integration of these two indices will form the Ecology – Tourism Matrix (ETM), outlining the base for tourism planning in an environmentally sensitive destination. The ETM Matrix leads to a classification of tourism nodes according to its Conservation Significance and Tourism Significance. The spatial integration of such nodes based on the Hub & Spoke Principle constitutes sub – regions within the STZ. Ensuing analyses lead to specific guidelines for the STZ as a whole, specific tourism nodes, hubs and sub-regions. The study results in a multi – dimensional output, viz., (1) Classification system for tourism nodes in an environmentally sensitive region/ destination (2) Conservation / Tourism Development Strategies and Guidelines for the micro and macro regions and (3) A Sustainable Tourism Planning Tool particularly for Ecologically Sensitive Destinations, which can be adapted for other destinations as well.

Keywords: Tourism, Environment, Spatial Planning, Model

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640 Detection and Pose Estimation of People in Images

Authors: Mousa Mojarrad, Amir Masoud Rahmani, Mehrab Mohebi

Abstract:

Detection, feature extraction and pose estimation of people in images and video is made challenging by the variability of human appearance, the complexity of natural scenes and the high dimensionality of articulated body models and also the important field in Image, Signal and Vision Computing in recent years. In this paper, four types of people in 2D dimension image will be tested and proposed. The system will extract the size and the advantage of them (such as: tall fat, short fat, tall thin and short thin) from image. Fat and thin, according to their result from the human body that has been extract from image, will be obtained. Also the system extract every size of human body such as length, width and shown them in output.

Keywords: Analysis of Image Processing, Canny Edge Detection, Human Body Recognition, Measurement, Pose Estimation, 2D Human Dimension.

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639 Probabilistic Center Voting Method for Subsequent Object Tracking and Segmentation

Authors: Suryanto, Hyo-Kak Kim, Sang-Hee Park, Dae-Hwan Kim, Sung-Jea Ko

Abstract:

In this paper, we introduce a novel algorithm for object tracking in video sequence. In order to represent the object to be tracked, we propose a spatial color histogram model which encodes both the color distribution and spatial information. The object tracking from frame to frame is accomplished via center voting and back projection method. The center voting method has every pixel in the new frame to cast a vote on whereabouts the object center is. The back projection method segments the object from the background. The segmented foreground provides information on object size and orientation, omitting the need to estimate them separately. We do not put any assumption on camera motion; the proposed algorithm works equally well for object tracking in both static and moving camera videos.

Keywords: center voting, back projection, object tracking, size adaptation, non-stationary camera tracking.

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638 A Robust Image Steganography Method Using PMM in Bit Plane Domain

Authors: Souvik Bhattacharyya, Aparajita Khan, Indradip Banerjee, Gautam Sanyal

Abstract:

Steganography is the art and science that hides the information in an appropriate cover carrier like image, text, audio and video media. In this work the authors propose a new image based steganographic method for hiding information within the complex bit planes of the image. After slicing into bit planes the cover image is analyzed to extract the most complex planes in decreasing order based on their bit plane complexity. The complexity function next determines the complex noisy blocks of the chosen bit plane and finally pixel mapping method (PMM) has been used to embed secret bits into those regions of the bit plane. The novel approach of using pixel mapping method (PMM) in bit plane domain adaptively embeds data on most complex regions of image, provides high embedding capacity, better imperceptibility and resistance to steganalysis attack.

Keywords: PMM (Pixel Mapping Method), Bit Plane, Steganography, SSIM, KL-Divergence.

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637 A Modified Spiral Search Algorithm and Its Embedded System Architecture Design

Authors: Nikolaos Kroupis, Minas Dasygenis, Dimitrios Soudris, Antonios Thanailakis

Abstract:

One of the most growing areas in the embedded community is multimedia devices. Multimedia devices incorporate a number of complicated functions for their operation, like motion estimation. A multitude of different implementations have been proposed to reduce motion estimation complexity, such as spiral search. We have studied the implementations of spiral search and identified areas of improvement. We propose a modified spiral search algorithm, with lower computational complexity compared to the original spiral search. We have implemented our algorithm on an embedded ARM based architecture, with custom memory hierarchy. The resulting system yields energy consumption reduction up to 64% and performance increase up to 77%, with a small penalty of 2.3 dB, in average, of video quality compared with the original spiral search algorithm.

Keywords: Spiral Search, Motion Estimation, Embedded Systems, Low Power

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636 Solving of the Fourth Order Differential Equations with the Neumann Problem

Authors: Marziyeh Halimi, Roushanak Lotfikar, Simin Mansouri Borojeni

Abstract:

In this paper we considered the Neumann problem for the fourth order differential equation. First we define the weighted Sobolev space 2 Wα and generalized solution for this equation. Then we consider the existence and uniqueness of the generalized solution, as well as give the description of the spectrum and of the domain of definition of the corresponding operator.

Keywords: Neumann problem, weighted Sobolev spaces, generalized solution, spectrum of linear operators.2000 mathematic subject classification: 34A05, 34A30.

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635 Adaptive Gaussian Mixture Model for Skin Color Segmentation

Authors: Reza Hassanpour, Asadollah Shahbahrami, Stephan Wong

Abstract:

Skin color based tracking techniques often assume a static skin color model obtained either from an offline set of library images or the first few frames of a video stream. These models can show a weak performance in presence of changing lighting or imaging conditions. We propose an adaptive skin color model based on the Gaussian mixture model to handle the changing conditions. Initial estimation of the number and weights of skin color clusters are obtained using a modified form of the general Expectation maximization algorithm, The model adapts to changes in imaging conditions and refines the model parameters dynamically using spatial and temporal constraints. Experimental results show that the method can be used in effectively tracking of hand and face regions.

Keywords: Face detection, Segmentation, Tracking, Gaussian Mixture Model, Adaptation.

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634 Smartphones for In-home Diagnostics in Telemedicine

Authors: Nálevka Petr

Abstract:

Many contemporary telemedical applications rely on regular consultations over the phone or video conferencing which consumes valuable resources such as the time of the doctors. Some applications or treatments allow automated diagnostics on the patient side which only notifies the doctors in case a significant worsening of patient’s condition is measured. Such programs can save valuable resources but an important implementation issue is how to ensure effective and cheap diagnostics on the patient side. First, specific diagnostic devices on patient side are expensive and second, they need to be user-˜friendly to encourage patient’s cooperation and reduce errors in usage which may cause noise in diagnostic data. This article proposes the use of modern smartphones and various build-in or attachable sensors as universal diagnostic devices applicable in a wider range of telemedical programs and demonstrates their application on a case-study – a program for schizophrenic relapse prevention.

Keywords: Smartphones, Actigraphy, Telemedicine, In-home Diagnostics

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633 Design and Implementation of a Neural Network for Real-Time Object Tracking

Authors: Javed Ahmed, M. N. Jafri, J. Ahmad, Muhammad I. Khan

Abstract:

Real-time object tracking is a problem which involves extraction of critical information from complex and uncertain imagedata. In this paper, we present a comprehensive methodology to design an artificial neural network (ANN) for a real-time object tracking application. The object, which is tracked for the purpose of demonstration, is a specific airplane. However, the proposed ANN can be trained to track any other object of interest. The ANN has been simulated and tested on the training and testing datasets, as well as on a real-time streaming video. The tracking error is analyzed with post-regression analysis tool, which finds the correlation among the calculated coordinates and the correct coordinates of the object in the image. The encouraging results from the computer simulation and analysis show that the proposed ANN architecture is a good candidate solution to a real-time object tracking problem.

Keywords: Image processing, machine vision, neural networks, real-time object tracking.

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632 Fault-Tolerant Control Study and Classification: Case Study of a Hydraulic-Press Model Simulated in Real-Time

Authors: Jorge Rodriguez-Guerra, Carlos Calleja, Aron Pujana, Iker Elorza, Ana Maria Macarulla

Abstract:

Society demands more reliable manufacturing processes capable of producing high quality products in shorter production cycles. New control algorithms have been studied to satisfy this paradigm, in which Fault-Tolerant Control (FTC) plays a significant role. It is suitable to detect, isolate and adapt a system when a harmful or faulty situation appears. In this paper, a general overview about FTC characteristics are exposed; highlighting the properties a system must ensure to be considered faultless. In addition, a research to identify which are the main FTC techniques and a classification based on their characteristics is presented in two main groups: Active Fault-Tolerant Controllers (AFTCs) and Passive Fault-Tolerant Controllers (PFTCs). AFTC encompasses the techniques capable of re-configuring the process control algorithm after the fault has been detected, while PFTC comprehends the algorithms robust enough to bypass the fault without further modifications. The mentioned re-configuration requires two stages, one focused on detection, isolation and identification of the fault source and the other one in charge of re-designing the control algorithm by two approaches: fault accommodation and control re-design. From the algorithms studied, one has been selected and applied to a case study based on an industrial hydraulic-press. The developed model has been embedded under a real-time validation platform, which allows testing the FTC algorithms and analyse how the system will respond when a fault arises in similar conditions as a machine will have on factory. One AFTC approach has been picked up as the methodology the system will follow in the fault recovery process. In a first instance, the fault will be detected, isolated and identified by means of a neural network. In a second instance, the control algorithm will be re-configured to overcome the fault and continue working without human interaction.

Keywords: Fault-tolerant control, electro-hydraulic actuator, fault detection and isolation, control re-design, real-time.

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631 Efficient Utilization of Unmanned Aerial Vehicle (UAV) for Fishing through Surveillance for Fishermen

Authors: T. Ahilan, V. Aswin Adityan, S. Kailash

Abstract:

UAV’s are small remote operated or automated aerial surveillance systems without a human pilot aboard. UAV’s generally finds its use in military and special operation application, a recent growing trend in UAV’s finds its application in several civil and nonmilitary works such as inspection of power or pipelines. The objective of this paper is the augmentation of a UAV in order to replace the existing expensive sonar (Sound Navigation And Ranging) based equipment amongst small scale fisherman, for whom access to sonar equipment are restricted due to limited economic resources. The surveillance equipment’s present in the UAV will relay data and GPS (Global Positioning System) location onto a receiver on the fishing boat using RF signals, using which the location of the schools of fishes can be found. In addition to this, an emergency beacon system is present for rescue operations and drone recovery.

Keywords: GPS, RF signals, School of fish, Sonar, Surveillance UAV, Video stream.

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630 Atrial Fibrillation Analysis Based on Blind Source Separation in 12-lead ECG

Authors: Pei-Chann Chang, Jui-Chien Hsieh, Jyun-Jie Lin, Feng-Ming Yeh

Abstract:

Atrial Fibrillation is the most common sustained arrhythmia encountered by clinicians. Because of the invisible waveform of atrial fibrillation in atrial activation for human, it is necessary to develop an automatic diagnosis system. 12-Lead ECG now is available in hospital and is appropriate for using Independent Component Analysis to estimate the AA period. In this research, we also adopt a second-order blind identification approach to transform the sources extracted by ICA to more precise signal and then we use frequency domain algorithm to do the classification. In experiment, we gather a significant result of clinical data.

Keywords: 12-Lead ECG, Atrial Fibrillation, Blind SourceSeparation, Kurtosis

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629 Active Learning Strategies and Academic Achievement among Some Psychology Undergraduates in Barbados

Authors: Grace Adebisi Fayombo

Abstract:

This study investigated the relationships between the active learning strategies (discussion, video clips, game show, role– play, five minute paper, clarification pauses, and small group) and academic achievement among a sample of 158 undergraduate psychology students in The University of the West Indies (UWI), Barbados. Results revealed statistically significant positive correlations between active learning strategies and students’ academic achievement; so also the active learning strategies contributed 22% (Rsq=0.222) to the variance being accounted for in academic achievement and this was found to be statistically significant (F(7,150) = 6.12, p < .05). Additionally, group work emerged as the best active learning strategy and had the highest correlation with the students’ academic achievement. These results were discussed in the light of the importance of the active learning strategies promoting academic achievement among the university students.

Keywords: Academic achievement, active learning strategies, psychology, undergraduates.

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628 Heterogeneity-Aware Load Balancing for Multimedia Access over Wireless LAN Hotspots

Authors: Yen-Cheng Chen, Gong-Da Fang

Abstract:

Wireless LAN (WLAN) access in public hotspot areas becomes popular in the recent years. Since more and more multimedia information is available in the Internet, there is an increasing demand for accessing multimedia information through WLAN hotspots. Currently, the bandwidth offered by an IEEE 802.11 WLAN cannot afford many simultaneous real-time video accesses. A possible way to increase the offered bandwidth in a hotspot is the use of multiple access points (APs). However, a mobile station is usually connected to the WLAN AP with the strongest received signal strength indicator (RSSI). The total consumed bandwidth cannot be fairly allocated among those APs. In this paper, we will propose an effective load-balancing scheme via the support of the IAPP and SNMP in APs. The proposed scheme is an open solution and doesn-t need any changes in both wireless stations and APs. This makes load balancing possible in WLAN hotspots, where a variety of heterogeneous mobile devices are employed.

Keywords: Wireless LAN, Load balancing, IAPP, SNMP.

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627 Object Tracking using MACH filter and Optical Flow in Cluttered Scenes and Variable Lighting Conditions

Authors: Waqar Shahid Qureshi, Abu-Baqar Nisar Alvi

Abstract:

Vision based tracking problem is solved through a combination of optical flow, MACH filter and log r-θ mapping. Optical flow is used for detecting regions of movement in video frames acquired under variable lighting conditions. The region of movement is segmented and then searched for the target. A template is used for target recognition on the segmented regions for detecting the region of interest. The template is trained offline on a sequence of target images that are created using the MACH filter and log r-θ mapping. The template is applied on areas of movement in successive frames and strong correlation is seen for in-class targets. Correlation peaks above a certain threshold indicate the presence of target and the target is tracked over successive frames.

Keywords: Correlation filters, optical flow, log r-θ mapping.

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626 Analysing and Classifying VLF Transients

Authors: Ernst D. Schmitter

Abstract:

Monitoring lightning electromagnetic pulses (sferics) and other terrestrial as well as extraterrestrial transient radiation signals is of considerable interest for practical and theoretical purposes in astro- and geophysics as well as meteorology. Managing a continuous flow of data, automation of the analysis and classification process is important. Features based on a combination of wavelet and statistical methods proved efficient for this task and serve as input into a radial basis function network that is trained to discriminate transient shapes from pulse like to wave like. We concentrate on signals in the Very Low Frequency (VLF, 3 -30 kHz) range in this paper, but the developed methods are independent of this specific choice.

Keywords: Transient signals, statistics, wavelets, neural networks

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625 Real Time Detection, Tracking and Recognition of Medication Intake

Authors: H. H. Huynh, J. Meunier, J.Sequeira, M.Daniel

Abstract:

In this paper, the detection and tracking of face, mouth, hands and medication bottles in the context of medication intake monitoring with a camera is presented. This is aimed at recognizing medication intake for elderly in their home setting to avoid an inappropriate use. Background subtraction is used to isolate moving objects, and then, skin and bottle segmentations are done in the RGB normalized color space. We use a minimum displacement distance criterion to track skin color regions and the R/G ratio to detect the mouth. The color-labeled medication bottles are simply tracked based on the color space distance to their mean color vector. For the recognition of medication intake, we propose a three-level hierarchal approach, which uses activity-patterns to recognize the normal medication intake activity. The proposed method was tested with three persons, with different medication intake scenarios, and gave an overall precision of over 98%.

Keywords: Activity recognition, background subtraction, tracking, medication intake, video surveillance

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624 Students’ Awareness of the Use of Poster, Power Point and Animated Video Presentations: A Case Study of Third Year Students of the Department of English of Batna University

Authors: Bahloul Amel

Abstract:

The present study debates students’ perceptions of the use of technology in learning English as a Foreign Language. Its aim is to explore and understand students’ preparation and presentation of Posters, PowerPoint and Animated Videos by drawing attention to visual and oral elements. The data is collected through observations and semi-structured interviews and analyzed through phenomenological data analysis steps. The themes emerged from the data, visual learning satisfaction in using information and communication technology, providing structure to oral presentation, learning from peers’ presentations, draw attention to using Posters, PowerPoint and Animated Videos as each supports visual learning and organization of thoughts in oral presentations.

Keywords: Animated Videos, EFL, Posters, PowerPoint presentations, Visual Learning.

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623 Single Frame Supercompression of Still Images,Video, High Definition TV and Digital Cinema

Authors: Mario Mastriani

Abstract:

Super-resolution is nowadays used for a high-resolution image produced from several low-resolution noisy frames. In this work, we consider the problem of high-quality interpolation of a single noise-free image. Such images may come from different sources, i.e., they may be frames of videos, individual pictures, etc. On the other hand, in the encoder we apply a downsampling via bidimen-sional interpolation of each frame, and in the decoder we apply a upsampling by which we restore the original size of the image. If the compression ratio is very high, then we use a convolutive mask that restores the edges, eliminating the blur. Finally, both, the encoder and the complete decoder are implemented on General-Purpose computation on Graphics Processing Units (GPGPU) cards. In fact, the mentioned mask is coded inside texture memory of a GPGPU.

Keywords: General-Purpose computation on Graphics ProcessingUnits, Image Compression, Interpolation, Super-resolution.

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622 Semantic Web as an Enabling Technology for Better e-Services Addoption

Authors: Luka Pavlič, Marjan Heričko

Abstract:

E-services have significantly changed the way of doing business in recent years. We can, however, observe poor use of these services. There is a large gap between supply and actual eservices usage. This is why we started a project to provide an environment that will encourage the use of e-services. We believe that only providing e-service does not automatically mean consumers would use them. This paper shows the origins of our project and its current position. We discuss the decision of using semantic web technologies and their potential to improve e-services usage. We also present current knowledge base and its real-world classification. In the paper, we discuss further work to be done in the project. Current state of the project is promising.

Keywords: E-Services, E-Services Repository, Ontologies, Semantic Web

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621 High Performance VLSI Architecture of 2D Discrete Wavelet Transform with Scalable Lattice Structure

Authors: Juyoung Kim, Taegeun Park

Abstract:

In this paper, we propose a fully-utilized, block-based 2D DWT (discrete wavelet transform) architecture, which consists of four 1D DWT filters with two-channel QMF lattice structure. The proposed architecture requires about 2MN-3N registers to save the intermediate results for higher level decomposition, where M and N stand for the filter length and the row width of the image respectively. Furthermore, the proposed 2D DWT processes in horizontal and vertical directions simultaneously without an idle period, so that it computes the DWT for an N×N image in a period of N2(1-2-2J)/3. Compared to the existing approaches, the proposed architecture shows 100% of hardware utilization and high throughput rates. To mitigate the long critical path delay due to the cascaded lattices, we can apply the pipeline technique with four stages, while retaining 100% of hardware utilization. The proposed architecture can be applied in real-time video signal processing.

Keywords: discrete wavelet transform, VLSI architecture, QMF lattice filter, pipelining.

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